HONOR DNY-NX9
Geekbench AI Score
694
Single Precision Score
692
Half Precision Score
1359
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 13 2025 12:59 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR DNY-NX9 |
| Model ID | HONOR DNY-NX9 |
| Motherboard | crow |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.63 GHz |
| Memory Information | |
|---|---|
| Size | 7.23 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
731
135.9 IPS |
|
|
Image Classification (HP)
|
100% |
752
139.9 IPS |
|
|
Image Classification (Q)
|
100% |
1959
364.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
705
11.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
700
11.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1929
31.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1882
2.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
1836
2.14 IPS |
|
|
Pose Estimation (Q)
|
84% |
2648
3.14 IPS |
|
|
Object Detection (SP)
|
98% |
368
29.3 IPS |
|
|
Object Detection (HP)
|
98% |
366
29.1 IPS |
|
|
Object Detection (Q)
|
83% |
774
62.5 IPS |
|
|
Face Detection (SP)
|
100% |
655
7.78 IPS |
|
|
Face Detection (HP)
|
100% |
668
7.94 IPS |
|
|
Face Detection (Q)
|
95% |
1737
20.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
890
6.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
895
6.91 IPS |
|
|
Depth Estimation (Q)
|
64% |
2077
19.0 IPS |
|
|
Style Transfer (SP)
|
89% |
2203
2.86 IPS |
|
|
Style Transfer (HP)
|
89% |
2199
2.85 IPS |
|
|
Style Transfer (Q)
|
98% |
5310
6.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
473
17.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
483
17.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1418
52.5 IPS |
|
|
Text Classification (SP)
|
100% |
260
346.8 IPS |
|
|
Text Classification (HP)
|
99% |
257
343.0 IPS |
|
|
Text Classification (Q)
|
88% |
425
573.3 IPS |
|
|
Machine Translation (SP)
|
100% |
461
7.94 IPS |
|
|
Machine Translation (HP)
|
100% |
440
7.58 IPS |
|
|
Machine Translation (Q)
|
50% |
241
8.55 IPS |
